Studying Stem Cell Systems through Integrated 'Omics Data

Abstract:

Stem cells balance the maintenance of pleuripotency and readiness to differentiate. Upon initiation of differentiation, they must be ready to proceed along a multiplicity of fates. Conflicting signals between states must be regulated during transitions, and this regulation may be critical to completing the transition. Wnt signaling governs both maintenance of pleuripotency (at low doses) and differentiation (at higher doses) in stem cells. Our recently reported discovery and characterization of a new, essential regulator of the Wnt signaling pathway provided a missing piece in how stem cells initiate differentiation. Time series RNA-seq data of WNT3a-treated human embryonic stem cells revealed a new transcription factor that regulates Wnt-response by displacing a ubiquitous transcription factor to repress gene expression. ChIP-seq data for each transcription factor revealed specific genes targeted by this negative feedback system. Genome-editing disabled the new transcription factor and confirmed the negative feedback loop. This talk will (1) trace how the regulatory loop emerged from the multiple 'omics datas and also cover two related studies that used the interpretation of gene expression patterns through RNA-seq to explore (2) Wnt-pathway regulation of "head-tail" organization during differentiation, and (3) dose-dependent Wnt-regulation of lineage specificity. The latter study engineered and characterized a new line of intermediate mesodermal progenitor cells positioned to incorporate and contribute to kidney.

Bio:

Dr. Gaasterland leads a research program aimed to develop and apply methods to identify genes and the impact of their genetic and evolutionary variation on regulation of transcription and on protein domain structure and function. Dr. Gaasterland has extensive experience with microbial genome sequencing and annotation, use of RNA-seq data to identify genes in assembled genomes from novel organisms, software tools to detect horizontally transferred genes in microbes, the management and analysis of large next-generation high-throughput sequencing datasets, and the sequencing and analysis of marine microbial, eukaryotic, and human genomes. Accomplishments in these areas as well as her early career work in deductive databases is reflected in over 100 refereed publications. Dr. Gaasterland trained as a computer scientist with emphasis in databases, automated reasoning and reasoning with uncertain information. With a Department of Energy postdoctoral fellowship, she transitioned from pure computer science into the application of methods in databases and artificial intelligence to the interpretation and analysis of genomic sequence and gene expression data. Since receiving the Presidential Early Career Award in Science and Engineering (PECASE) in 2000, she has been continuously funded by the National Science Foundation to develop and use methods in computational genomics, and has participated as PI or co-PI on a series of biomedical grants from the NIH. She is PI of NIH/NEI awards to sequence and analyze variation in protein coding exons genome-wide for 400 primary open angle glaucoma cases, as a member of the NEIGHBOR Consortium at the Massachusetts Eye and Ear Institute and the NHGRI Medical Sequencing program.